Plenary Speakers

Synchronization in populations of moving oscillators

Talk abstract: Here, we will show results obtained in our group concerning synchronization of populations of moving oscillators. On the one hand, populations of identical Kuramoto oscillators that move randomly on a plane, without considering excluded volume effects, enables to obtain analytical results for the time needed to synchronize [1]; later on, we have extended this framework to locally interacting self-propelled particles for which synchronization generically proceeds through coarsening verifying the dynamic scaling hypothesis, with the same scaling laws as the the 2d XY model following a quench [2]. Our results shed light into the generic nature of synchronization in time-dependent networks, providing an efficient way to understand more specific situations involving interacting mobile agents. Alternatively, we have also investigated synchronization in populations of integrate and fire oscillators, showing that under restrictive conditions of connectivity, the time needed for the population to synchronize is not a monotonous function of velocity [3, 4].

Albert Díaz-Guilera got his degree in Physics at Universitat de Barcelona (1983). PhD in Science at Universitat Autonoma de Barcelona (1987). Postdoctoral stays in Gorlaeus Laboratories (Leiden, The Netherlands) and “Centre de Physique de Solide” (Sherbrooke, Canada). His research is currently focused on general aspects of complexity, particularly in complex networks. He is currently the Director of the Universitat de Barcelona’s Institute of Complex Systems (UBICS). Being by education a statistical physicist, his research lines had been broadening to cover aspects in many different fields: biology, economy, social sciences, computer science, linguistics. Direct collaborations with scientists with different backgrounds have been possible by means of stays in different centers (Mathematics at Imperial College London, Chemical and Biological Engineering at Northwestern University, Ecologia UNAM, Potsdam Institute of Climatology, Potsdam Psychology, Sociology at ETHZ). He is the author of more than 100 articles in physics and interdisciplinary journals with over 10,000 citations [Google Scholar] and has given about one hundred talks at conferences and research centres. He is also the PI of projects from Catalan and Spanish Governments and EU and the leader of the research group PHYSCOMP2 (http://clabb.eu).
More information can be found at: www.diaz-guilera.net

Chaos-based Quantum Control

Talk abstract: Quantum chaos is referred to the study of quantum manifestations of systems that are chaotic in the classical limit. Most previous research in the field of quantum chaos focused on the non-relativistic quantum regime. Recently the field of relativistic quantum chaos has emerged, due to the tremendous development of research on graphene and topological insulators. Phenomena such as relativistic quantum scarring, chaotic scattering, and tunnelling have been explored. The speaker will discuss a number of fundamental issues in relativistic quantum chaos, but from the perspective of quantum control or modulation: how classical chaos can be exploited to harness relativistic quantum behaviours in Dirac fermion and graphene systems? Transport through quantum dot and resonant tunnelling will be used as two prototypical examples to illustrate the principle that chaos-based quantum control can be advantageous and experimentally feasible.

Celso Grebogi is the Sixth Century Chair in Nonlinear and Complex systems at the University of Aberdeen, UK. He is also the Founder and Director of the Institute for Complex Systems and Mathematical Biology, Non-executive Director (Mitglied) of the Max-Planck-Society, and Professor (part-time) at the Xi’an University of Technology. He is a leading expert in chaotic dynamics. He was previously with the University of Sao Paulo, Brazil, as Professor of Physics, and, before that, at University of California, Berkeley, as Postdoc and with the University of Maryland as Professor of Mathematics. Professor Grebogi’s research in chaotic dynamical systems involves bridging the gap between abstract concepts, on the one hand, and the scientific disciplines, and engineering, medical and social fields where the applications occur, on the other hand. His research in systems biology integrates mathematical developments with biological experiments. He has made an enormous international impact with his seminal work in the area of chaotic control; he was awarded the Thomson-Reuters Citation Laureate for this work, and it was also selected by the American Physical Society as a milestone in the last 50 years. His scientific accomplishments include over 450 publications for which he received numerous distinctions including multiple Doctor Honoris Causa and five Honorary Professorships in China, the Humboldt Senior Prize, Fulbright Fellowship, and Toshiba Chair as a World-renown Scholar. He is Fellow at various scientific societies, including the Royal Society of Edinburgh, The World Academy of Sciences, the Brazilian Academy of Sciences, and the American Physical Society. He has 22,000 citations and h-index = 71 in the Thomson-Reuters Web of Science (36,000 citations and h-index = 85 in Google Scholar).

Talk abstract: The evolution equation for the magnetization M of a ferromagnetic material is the Landau-Lifshitz-Gilbert (LLG) equation, where the effective field He includes the external field and the effective field due to spin interactions. We study the asymptotics of this equation for ferromagnets with an easy plane and in-plane easy axis. Two regimes are found, depending on the strength of the easy plane. For moderately strong easy plane the dynamics can be reduced to a reaction diffusion equation and the speed of the domain walls increases linearly with the applied field. Similar results have been found for thin nanotubes. The approach followed allows to include the Dzyaloshinski Moriya interaction which modifies the magnetization profile but not the speed. For a stronger easy plane the dynamics is governed by a hyperbolic reaction diffusion equation which predicts that the speed at first increases linearly with the applied field and then reaches a plateau. This behavior describes what has been observed numerically and experimentally in some materials. Work in progress for thin nanotubes will also be described where we expect similar behavior. In both, the moderate and strong easy plane cases, a transition from pushed to a pulled front is found as the applied field increases beyond a critical value which depends on the uniaxial anisotropy constant. This transition slows down the domain wall. We shall also discuss the relation of the exact Walker solution to reaction diffusion dynamics and explain its recently found instability as the magnetic field increases beyond a critical value as a transition from a pushed to a pulled regime.

Cristina Depassier is a Professor of Physics at the Institute of Physics, Pontificia Universidad Catolica de Chile, Santiago de Chile. She has done extensive work on the propagation of fronts of reaction-diffusion equations. Her current interests include the study of the dynamics of domain walls in ferromagnetic materials in the micromagnetic model.

Signal encoding and transmission by noisy coupled neurons

Sensory neurons encode and transmit information of external inputs in their spike sequences; however, how the information of a weak signal is encoded in the presence of noise remains poorly understood. Different encoding mechanisms can be expected to be functional under different conditions. In this talk I will focus on a conceptually simple problem: how neurons encode a weak periodic input? First, I will focus in an individual neuron. I will present results of simulations of the stochastic FitzHugh-Nagumo (FHN) model that suggest that, when the neuron perceives the signal, it can encode it’s period and amplitude in the probabilities of more-expressed and less-expressed spike patterns, which are defined by the relative timing of the spikes [1]. Then, I will discuss how a second neuron, which does not perceive the signal, affects the detection and the encoding of the signal, done by the first neuron. I will present results of simulations of two noisy FHN neurons. Simulations suggest that the neuron that perceives the signal fires a spike train which also has preferred and infrequent patterns carrying the signal information [2]. Therefore, signal encoding in symbolic spike patterns is robust to coupling, and thus, it can be a plausible mechanism of signal encoding. Finally, I will discuss ongoing efforts devoted to understand the encoding of weak signals by small ensembles of neurons, with modular coupling structure.

Cristina Masoller is an Associate Professor of Physics at the Universitat Politècnica de Catalunya (UPC) in Barcelona, Spain. She is interested in inter-disciplinary research in dynamical complex systems. Her research topics include laser dynamics, neuronal models and excitability, synchronization, complex networks, time-series analysis, climate data analysis, and extreme events. Se received both Bachelor’s and Master’s degrees in Physics from Uruguay’s Universidad de la República and her Ph.D. from Bryn Mawr College in the United States. She received an ICREA Academia award from Generalitat de Catalunya (2010 and 2015) and she is a fellow of the Optical Society.

Life at the edge: complexity and criticality in biological function

Why life is complex and – importantly – what is the origin of the over abundance of complexity in nature. This is a fundamental scientific question which, paraphrasing the late Per Bak, “is screaming to be answered but seldom is even being asked”. In this lecture we review successful attempts to understand the origins of complex biological problems from the perspective of critical phenomena. To illustrate the approach across three scales cases are discussed, namely the large scale brain dynamics, the characterisation of spontaneous fluctuations of proteins and the complexity of the cell mitochondria network.

Dante R. Chialvo is Full Professor of Medical Physics at the Universidad Nacional de San Martin (UNSAM) in Argentina where he leads the Center for Complex Systems & Brain Sciences. His career spans more than two decades at top Universities though the globe, including SUNY, Northwestern University, UCLA at Los Angeles and the Santa Fe Institute among many others. He has published extensively on the dynamics of complex phenomena in biology. In neuroscience, Dr. Chialvo’s is known for his work dedicated to understand the large-scale organisation of the brain in health and disease and the development of mathematical tools to better describe the state of mind. Together with the late Per Bak in the 90’s he spread the study of brain dynamics as a critical phenomena. He is a Fellow of the American Physical Society and received a Fulbright US Scholar Award. His publications have more than 11000 citations and he has an h-index of 46 [Google Scholar].

Inducing dreams in oscine birds

Talk abstract: The coordination of complex vocal behaviors like oscine birdsong require fine interactions between sensory and motor programs. Here we show that in sleeping male zebra finches (Taeniopygia guttata), the activity of the song system selectively evoked by playbacks of their own song can be detected in the syrinx. Electromyograms (EMG) of a syringeal muscle show playback evoked patterns similar to those recorded during song production. Using this readout we studied the activation elicited by different auditory stimuli. We found that synthetic versions of the bird’s song, rendered by a physical model of the avian phonation apparatus, evoked similar patterns. Modifications of autogenous or synthetic songs reduce the response probability, but when present, the elicited activity patterns match execution patterns. This builds on previous work, where spontaneous, song-like patterns were observed during sleep, at the level of the syrinx.

Gabriel Mindlin is a Professor at the Physics Department of the School of Sciences at the Universidad de Buenos Aires, Argentina, and a researcher of CONICET. He works in the Physics of birdsong production, running a laboratory where the problem is adressed from a variety of perspectives. These include theoretical and experimental studies of the biomechanics of avian phonation, as well as electro-physiological measurements in different areas of the song system.

Robust chaos: a tale of blenders, their computation, and their destruction

Talk abstract: A blender is an intricate geometric structure of a three- or higher-dimensional diffeomorphism. Its characterising feature is that its invariant manifolds behave as geometric objects of a dimension that is larger than expected from the dimensions of the manifolds themselves. We introduce a family of three-dimensional Hénon-like maps and study how it gives rise to an explicit example of a blender. The map has two saddle fixed points. Their associated stable and unstable manifolds consist of points for which the sequence of images or pre-images converges to one of the saddle points; such points lie on curves or surfaces, depending on the number of stable eigenvalues of the Jacobian at the saddle points. We employ advanced numerical techniques to compute one-dimensional stable and unstable manifolds to very considerable arclengths. In this way, we not only present the first images of an actual blender but also obtain a convincing numerical test for the blender property. This allows us to present strong numerical evidence for the existence of the blender over a larger parameter range, as well as its disappearance and geometric properties beyond this range. We will also discuss the relevance of the blender property for chaotic attractors.

This is joint work with Stephanie Hittmeyer and Bernd Krauskopf (University of Auckland) and Katsutoshi Shinohara (Hitotsubashi University).

Hinke Osinga is Professor in Applied Mathematics at the University of Auckland, New Zealand. She is a Fellow of the Royal Society of New Zealand, Fellow of the New Zealand Mathematical Society, and Fellow of the Society for Industrial and Applied Mathematics. She is a specialist in dynamical systems theory and the development and application of numerical methods for computing invariant manifolds. Her work constitutes a significant contribution to manifold theory, for which she was awarded the Research Award of the New Zealand Mathematical Society. Her publications, illustrations, animations and outreach activities have made her famous worldwide in the mathematics and arts communities. Her international standing was recognised by her invitation to speak at the 2014 International Congress of Mathematicians.

In many situations ranging from blood flow to atomization of slurries in industrial processing, one encounters non-Newtonian fluids in turbulent conditions. Intuitively, in the inertial subrange, molecular stresses should have a negligible influence on the motion and size of the eddies, regardless of the rheological nature of the fluid. More precisely, even if a more complex constitutive law than a linear one is necessary to describe the stress-strain relation of a moving fluid, one should expect the statistical results obtained for the structure of Newtonian turbulence at the inertial subrange to remain valid. A relevant question that naturally arises is how the local rheological properties of the fluid must rearrange in space and time to comply with this alleged structural invariance. Here we investigate through Direct Numerical Simulations (DNS) the statistical properties of turbulent flows in the inertial subrange for non-Newtonian power-law fluids. Our results show that the structural invariance found for the vortex size distribution is achieved through a self-organized mechanism at the microscopic scale of the turbulent motion that adjusts, according to the rheological properties of the fluid, the ratio between the viscous dissipations inside and outside the vortices. Moreover, the deviations from the K41 theory of the structure functions’ exponents reveal that the anomalous scaling exhibits a systematic nonuniversal behavior with respect to the rheological properties of the fluids.

José S. Andrade Jr. is a full professor at the Physics Department of Universidade Federal do Ceará at Fortaleza in Brazil. His research interests include Complex Sytems, Statistical and Computational Physics, with emphasis on complex networks, percolation theory, fractals, transport phenomena in irregular and disordered systems, phase transitions and critical phenomena, computational fluid dynamics, diffusion and flow in porous media, pulmonary physiology, fragmentation and fracture formation. His publications have more than 7000 citations and he has an h-index of 46 [Google Scholar].

Talk abstract: We analyse climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. This concept is then applied to Monsoon data; in particular, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. Applying this method, we uncover a new mechanism of extreme floods in the eastern Central Andes which could be used for operational forecasts. Moreover, we analyze the Indian Summer Monsoon (ISM) and identify two regions of high importance. By estimating an underlying critical point, this leads to a substantially improved prediction of the onset of the ISM.

Jürgen Kurths is a German physicist and mathematician. He is a chair of the research domain Transdisciplinary Concepts of the Potsdam Institute for Climate Impact Research and Professor of Nonlinear Dynamics at the Institute of Physics at the Humboldt University, Berlin, Germany. His research is mainly concerned with nonlinear physics and complex systems sciences and their applications to challenging problems in Earth system, physiology, systems biology and engineering. Professor Kurths is an elected fellow of the American Physical Society and a member of the Academia Europaea. He received an Alexander von Humboldt research award and was awarded the L.F. Richardson Medal of the European Geosciences Union. He was bestowed with several Dr. honoris causa and several honorary professorships. He was a Burgers Visiting Professor at University of Maryland and is a Chapman Professor at the University of Alaska (Fairbanks). He is editor-in-chief of the AIP journal CHAOS. His h-index is 84 and he is a highly cited researcher with over 60,000 citations.

Katja Lindenberg earned her Ph.D. in Theoretical Physica from Cornell University in 1967 under the direction of Jim Krumhansl. She then did a two-year postdoc with Elliott Montroll at the University of Rochester, and joined the faculty at the University of California San Diego in 1969. From early on she has worked on stochastic processes and on reaction-diffusion phenomena. She also worked on polaron formation and transport and on pulse propagation in granular chains. In the past decade or so she has worked on non-equilibrium statistical mechanics, stochastic processes, synchronization and anti-synchronization phenomena in noisy systems, and stochastic thermodynamics. She has over 350 publications with more than 10,000 citations.

Fundamental energy limits in the physics of memories

In 1961, Rolf Landauer pointed out that resetting a binary memory requires a minimum energy of kTLn(2). However, once written, any memory is doomed to loose its content if no action is taken. To avoid memory losses, a refresh procedure is periodically performed. In this talk we present a theoretical and experimental study of sub-kT system to evaluate the minimum energy required to preserve one bit of information over time. Two main conclusions are drawn: i) in principle the energetic cost to preserve information for a fixed time duration with a given error probability can be arbitrarily reduced if the refresh procedure is performed often enough; ii) the Heisenberg uncertainty principle sets an upper bound on the memory lifetime: no memory can last forever.

Luca Gammaitoni is Professor of Experimental Physics at the University of Perugia, in Italy and the director of the Noise in Physical Systems (NiPS) Laboratory. He is also the founder of Wisepower srl a university spin-off company. He obtained the Ph.D. in Physics from the University of Pisa in 1990. Since then he has developed a wide international experience with collaborations both in Europe, Japan and the USA. His scientific interests span from noise phenomena in dynamical physical systems to non-equilibrium thermodynamics and energy transformations at micro and nanoscale, including the Physics of computing. He authored over 200 papers on top-level scientific journals and few books. He is also the author of 10 patents. His papers have been cited more than 34.000 times with an h-index 77 (Google Scholar). More info at www.nipslab.org.

Analysis of pedestrian evacuations: models and experiments

Talk abstract: When formulating the safety guidelines included in building codes the exit capacity in case of evacuation is among the critical parameters that must be considered. Most of the times, this capacity is consigned in terms of solely the exit times or equivalently the mean pedestrian flow rate through the designed exits. In this presentation we show that this measure may not provide an accurate characterization of an evacuating scenario and that an assessment of the fluctuations that occur during such process might provide a more sensitive and valuable information. For this reason, we suggest a simple way to partially assess the extent of information derived from these fluctuations on the basis ofthe statistical characterization of the time gaps between successive escapes through a door. We present both numerical and experimental results that while delimiting the validity range of the previous proposal, show that in any case it is better than only the measurement of the mean exit capacity.

Marcelo Kuperman does interdisciplinary research, linking physics and mathematics with biology and social sciences. He is interested in epidemiological phenomena, culture propagation, microeconomic behaviour, game theory, and structure formation and propagation, involving complex networks and nonlinear differential equations. He has a Ph. D. in Physics, is independent researcher of CONICET, and teaches at Instituto Balseiro. Presently, he is head of FiEstIn.

Talk abstract: Time series measured from real-world systems are generally noisy, complex and display statistical properties that evolve continuously over time. Here, we present a method that combines wavelet analysis and non-stationary surrogates to detect short-lived spatial coherent patterns from multivariate time-series. In contrast with standard methods, the surrogate data used here are realisations of a non-stationary stochastic process, preserving both the amplitude and time-frequency distributions of original data. We evaluate this framework on synthetic and real-world time series, and we show that it can provide useful insights into the time-resolved structure of spatially extended systems.

Mario Chavez has a background in complex systems applied to neurosciences (M.S. and Ph.D. degrees in France). After holding different postdoctoral positions (France & Italy) in the field of nonlinear physics and biomedical signal processing, he became a researcher at Centre National de la Recherche Scientifique (CNRS). His research activities concern new methodologies for characterising functional connectivity of electrophysiological signals recorded at multiple scales (LFP/MEG/EEG/SEEG/fMRI). He has developed a complex network-based framework to quantify the functional interactions between different neural structures involved in generation and propagation of epileptic activities.
More information on the research group can be found at: http://charpierlab.fr

Extreme events in turbulence: the case of stratified flows

Talk abstract: The definition of what an extreme event is can be different depending on the physical problem considered. In fluid dynamics, the phenomenon of intermittency is the sine qua non of turbulence, and calls for a precise definition of extreme events and for the development of specific theoretical tools to study them. Indeed, the complexity of a turbulent flow is often associated with the fact that turbulence comes in intermittent “gusts”. These intermittent gusts (or extreme events) are associated with non-Gaussian statistics of some physical quantity in the system. As such, intermittency is a highly spatially- and temporally-localized phenomenon, which thus requires high-resolution instrumentation, be it in the laboratory, in atmospheric observations, or in numerical simulations. In this talk I will discuss some tools from statistics and from dynamical systems that are regularly used to study intermittency and extreme events, including probability density functions of field increments, structure functions, and scaling exponents. As a particular example, I will focus on the problem of vertical drafts and mixing observed in stratified flows. In this problem, for values in parameter space relevant for the atmosphere and the oceans, I will show that non-stationary very large fluctuations of the vertical velocity take place spontaneously in the flow. This behavior can be captured by a simple model representing the competition between gravity waves on a fast time-scale, and non-linear steepening on a slower time-scale. The existence in these flows of a resonant regime characterized by enhanced large-scale intermittency, can then linked to the emergence of specific structures in the velocity and potential temperature fields.

Pablo Mininni received his diploma (1999) and doctoral degree (2003) in physics from the University of Buenos Aires (UBA) in Argentina. From 2004 to 2007 he was a postdoc and later a scientist at National Center for Atmospheric Research (NCAR) in Boulder, CO, USA, under the supervision of Annick Pouquet, David Montgomery, and Darryl Holm. He continued working for NCAR as a part-time scientist from 2007 to 2012. Since 2007 he is a researcher of CONICET (Argentina) and professor at the Physics Department at UBA, where he was also the chair of the department from 2011 to 2015. He received the national Houssay prize (Argentina) in 2010, and the ICTP prize (UNESCO/Italy) in 2012. He works on the numerical and theoretical study of turbulent flows, with applications in astrophysics, geophysics, and atmospheric sciences. In the field of fluid dynamics, his interests include extreme events, intermittency, the application of statistical methods for the characterization and analysis of turbulent flows, and spectral analysis of multi-scale and multi-physics phenomena. Applications include the solar cycle and turbulent dynamos, magnetic reconnection, rotating and stratified turbulence, and superfluid turbulence.

Delayed Dynamical Systems and Networks

Experiments on networks of coupled nonlinear oscillators are few and far between. A new experimental technique to generate networks of dynamical systems, small and large, with arbitrary coupling topology is described. This technique utilizes a space-time mapping of time-delay systems together with field programmable gate arrays (FPGA). Several aspects (advantages and limitations) of this technique are the ability to configure arbitrary networks (unidirectional or bidirectional), introduce controlled noise, and change network connections as desired. The dynamical nodes can be truly identical or non-identical and heterogeneous as desired. Larger networks slow down the operation of the system and are limited by the resources of the FPGAs employed. Our current experiments involve up to a few hundred nodes. Initially the system was demonstrated for networks of coupled maps; this has been extended to continuous time systems, and we will give examples of both types of operation. A recent effort has been made to implement reservoir computing processes on this experimental system. This may lead to hardware implementations of reservoir computing for specific problems.

Raj Roy is a professor of physics and Director of the Institute for Physical Science and Technology at the University of Maryland, United States. He earned his Ph.D. in 1981 from the University of Rochester. He is a Fellow of American Physical Society and a Fellow of the Optical Society of America. His research interests include the study of non-linear dynamics and noise in optical devices and systems relevant to very practical technological applications such as compact disk players, fibre optic communications, and the development of optical switching devices and laser arrays. His publications have received more than 13,000 citations and an h-index 58 (Google-scholar).

The calcium signaling dilemma: to propagate or not

Talk abstract: Calcium signals are ubiquitous. They are involved in a large variety of physiological processes. The versatility of calcium ions as a signaling agent relies on the variety of spatio-temporal distributions that the intracellular calcium concentration can display. While some signals remain spatially localized others propagate throughout the cell and even between cells to convey their message. Cells have different strategies to change the properties of their intracellular signals depending on various factors. In this talk I will discuss the main biophysical processes that underlie intracellular calcium signals and how they can be varied to elicit different signal types. I will focus, in particular, on the changes that occur during the maturation that transforms an oocyte into an egg that can eventually be fertilized, a process that requires the correct propagation of an intracellular calcium wave to start the sequence of cell divisions that leads to the formation of the embryo.

Interdependence and competition in dynamical multilayer networks

Talk abstract: From critical infrastructure, to physiology and the human brain, complex systems rarely occur in isolation. Instead, the functioning of some nodes in one system often promotes or inhibits the functioning of other nodes in another. I will illustrate a broadly applicable framework for interdependency and competition among dynamical units, and will discuss specific applications to synchronization and spreading processes in multilayer networks with interacting layers. Novel collective phenomena (which are absent in the isolated counterparts) are illustrated, including multi-stability, regions of coexistence, and macroscopic chaos. In interdependent dynamics, hysteretic behaviors with abrupt (hybrid and explosive) transitions appear, with universal dynamics that match interdependent percolation.

Stefano Boccaletti got his PhD in Physics at the University of Florence on 1995, and a PhD honoris causa at the Rey Juan Carlos University of Madrid on 2015. Currently, he is Senior Researcher at the Institute of Complex Systems of the CNR (Florence, Italy) and Honorary Professor of 7 Universities, among which the Northwestern Polytechnical University of Xi’an, in China. In the past, he has been Professor at the University of Navarre in Spain, Researcher at the National Institute of Optics in Italy, and senior Researcher at the Polytechnic University of Madrid. From 2007 to 2011 and from 2014 to April 2018 he served as Scientific Attache’ of the Italian Embassy in Israel. He is the author of 349 publications on Physics Journals, which received a total of more than 22,000 citations [Google Shcolar]. He is Editor in Chief of Chaos Solitons and Fractals (Elsevier). He has been invited to about 75 International Conferences and Seminars as a plenary lecturer, and he directly organized 45 International Workshops and events.

It Don’t Mean a Thing, If It Ain’t Got That Swing: Time Series Analysis of a Mystery

Talk abstract: The so-called swing feeling in jazz performances has puzzled musicologists and jazz critics for decades. For a long time it was believed that one can feel it, but one cannot explain it. More recently discussions focused on the role of microtiming deviations. Can we characterize this phenomenon using tools of nonlinear dynamics and statistical physics?

Theo Geisel is Director emeritus of the Max Planck Institute for Dynamics and Self-Organization, Professor of Theoretical Physics at the University of Göttingen and founding director of the Bernstein Center for Computational Neuroscience (BCCN) Göttingen. A recipient of the prestigious Gottfried Wilhelm Leibniz Prize and other prizes, he is a member of the Academy of Sciences and Humanities Göttingen and Fellow of the American Physical Society. He previously was Professor of Theoretical Physics at the University of Würzburg and the J.W. Goethe University of Frankfurt. Well known for his research on nonlinear dynamics and chaotic systems, e.g. for the discovery of Levy walks, he has worked in fields that include quantum chaos and semiconductor nanostructures, the spread of epidemics, and theoretical neuroscience. A classical and jazz musician performing on flute and saxophone, he is also investigating the psychophysics of musical rhythms.